code: def _init_NDArrayIter_data(data_type, is_image=False):
      if is_image:
          data = nd.random.uniform(0, 255, shape=(5000, 1, 28, 28))
          labels = nd.ones((5000, 1))
          return data, labels
      if data_type == "NDArray":
          data = nd.ones((1000, 2, 2))
          labels = nd.ones((1000, 1))
      else:
          data = np.ones((1000, 2, 2))
          labels = np.ones((1000, 1))
      for i in range(1000):
          data[i] = i / 100
          labels[i] = i / 100
      return data, labels
  
imports: import mxnet
  import mxnet.ndarray
  from mxnet.test_utils import *
  from mxnet.base import MXNetError
  import numpy
  import os
  import gzip
  import pickle
  import time
  import sys
  from common import assertRaises
  import pytest
  from itertools import zip_longest
label_desc: Use image node_id 6 for calling a global function with example usage: _init_NDArrayIter_data(data_type, is_image) and returns: data,  labels, data,  labels